Three-dimensional cardiac strain estimation using spatio-temporal elastic registration of ultrasound images: a feasibility study.
Current ultrasound methods for measuring myocardial strain are often limited to measurements in one or two dimensions. Cardiac motion and deformation however are truly 3-D. With the introduction of matrix transducer technology, 3-D ultrasound imaging of the heart has become feasible but suffers from low temporal and spatial resolution, making 3-D strain estimation challenging. In this paper, it is shown that automatic intensity-based spatio-temporal elastic registration of currently available 3-D volumetric ultrasound data sets can be used to measure the full 3-D strain tensor. The method was validated using simulated 3-D ultrasound data sets of the left ventricle (LV). Three types of data sets were simulated: a normal and symmetric LV with different heart rates, a more realistic asymmetric normal LV and an infarcted LV. The absolute error in the estimated displacement was between 0.47 +/-0.23 and 1.00 +/-0.59 mm, depending on heart rate and amount of background noise. The absolute error on the estimated strain was 9%-21% for the radial strain and 1%-4% for the longitudinal and circumferential strains. No large differences were found between the different types of data sets. The shape of the strain curves was estimated properly and the position of the infarcts could be identified correctly. Preliminary results on clinical data taken in vivo from three healthy volunteers and one patient with an apical aneurism confirmed these findings in a qualitative manner as the strain curves obtained with the proposed method have an amplitude and shape similar to what could be expected.
Elen
An
A
Department of Electrical Engineering, Medical Image Computing, Katholieke Universiteit Leuven, B-3000 Leuven, Belgium. an.elen@uz.kuleuven.ac.be
Choi
Hon Fai
HF
Loeckx
Dirk
D
Gao
Hang
H
Claus
Piet
P
Suetens
Paul
P
Maes
Frederik
F
D'hooge
Jan
J
D016477:Artifacts; D019560:Echocardiography, Three-Dimensional / Q000379:methods*; D006352:Heart Ventricles / Q000000981:diagnostic imaging / Q000503:physiopathology; D006801:Humans; D009068:Movement; D009200:Myocardial Contraction / Q000502:physiology*; D009203:Myocardial Infarction / Q000000981:diagnostic imaging; D010363:Pattern Recognition, Automated / Q000379:methods; D019047:Phantoms, Imaging; D012107:Research Design; D013382:Subtraction Technique; D013997:Time Factors